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XML + Semantics = DARPA Agent Markup Language (DAML). William Holmes, Dr. Paul Kogut Management & Data Systems Valley Forge, PA June 4, 2001. Roadmap. The Semantic Web Agents & Ontologies Object Management Group (OMG) Initiatives The D ARPA A gent M arkup L anguage (DAML) What is it?

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xml semantics darpa agent markup language daml

XML + Semantics = DARPA Agent Markup Language (DAML)

William Holmes, Dr. Paul Kogut

Management & Data Systems

Valley Forge, PA

June 4, 2001

roadmap
Roadmap
  • The Semantic Web
  • Agents & Ontologies
  • Object Management Group (OMG) Initiatives
  • The DARPA Agent Markup Language (DAML)
    • What is it?
    • How does it fit in? / What is its role?
  • LM M&DS UML-based Ontology Toolset (UBOT)
    • Ontology Design & Consistency Checking
    • Automated Annotation via AeroTextTM
semantic web the vision
Semantic Web: The Vision

Hi Pete, it’s Lucy. I’m at the doctor’s office.

Mom needs to see a specialist and then has

to have a series of physical therapy sessions.

Biweekly or something. Can you split the

chauffeuring with me?

Great! I’ll have my agent

set up the appointments.

Hello?

Sure Lucy.

RING … RING ...

* Berners-Lee, Hendler, Lassila “The Semantic Web” Scientific American, May 2001

the vision
The Vision

Lucy’s agent looks up several lists of

providers and checks for ones

in-plan for Mom’s insurance, within

a 20-mile radius of her home, and

with a rating of excellent or very good.

Schedule a treatment plan for Mom

using Pete and my schedules. Only use

providers that are in-plan for Mom’s

insurance, are within a 20-mile radius,

and have a rating of excellent or very good.

Lucy’s agent formulates a schedule

of appointments for therapists with

appointments available that fit

into Pete and Lucy’s schedule.

Lucy’s agent retrieves information

about Mom’s prescribed treatment

from the doctor’s agent.

Semantic Web

* Berners-Lee, Hendler, Lassila “The Semantic Web” Scientific American, May 2001

that s great but how
That’s Great but How?
  • Need Agents
    • Definition (Merriam-Webster):
      • one who is authorized to act for or in the place of another as a business representative
    • Provide a means of processing the volumes of information found on the web.
  • Need Ontologies
    • Definition:
      • Philosophy - A theory about the nature of existence.
      • A.I. - A formal definition of relations among terms.
    • Provide a “semantic grounding” for the web.
what are agents
What are Agents?
  • In software, “Agent” is used in many different ways:
      • persistent process/daemon:
      • mobile code
      • autonomous robots
      • “intelligent agent” - what makes it intelligent?
  • simple definitions that capture the essence of agents:
      • an Object that decides when to say go and when to say no - OMG
      • “programs that operate at a high enough semantic level that they can form new connections to other programs in order to get a job done” Burstein, McDermott
why agents

Internet / Intranet agents

I need to go to Fort Worth

on Monday for 3 days.

hotels

car rental

personal assistant

agent

itinerary, tickets & maps

maps

airlines

Why Agents?
  • Agents are the next generation of middleware
    • built on top of existing middleware (e.g., CORBA, EJB, Jini)
    • run-time integration via dynamic discovery and resource negotiation
      • emphasis on broker and facilitator agents (e.g. yellow pages)
  • Agents are the next generation user interface
    • more complex applications require personal assistant agents
    • multi-modal interfaces e.g. speech, handwriting, gestures
    • user specifies goals and agent handles details according to user preferences
why agents cont
Why Agents? (Cont.)
  • Agents are the next level of component abstraction
    • agents are components with attitudes
      • beliefs, desires, goals…*
    • agents interact like humans via speech acts
      • request, inform, promise
    • agents share a context for efficient communication
      • domain model ontologies are used at run-time
      • ontology agent/services - query, retrieve and translate ontologies

*Labrou, Finin, Peng “Agent Communication Languages:The Current Landscape” IEEE Intelligent Systems March/April 1999

examples of agent applications
Examples of Agent Applications*
  • personal assistant - digital secretary
    • travel arrangements
    • meeting schedule coordination
    • personalized information filtering
    • mobile computing
  • internet/intranet information retrieval/summarization
  • electronic commerce
  • enterprise workflow - e.g., sales, order processing, shipping
  • military command and control
  • synthetic characters (e.g., Extempo Systems, Virtual Personalities)
  • robots - manufacturing, office, domestic
  • design and engineering

*see Hendler “Is There An Intelligent Agent in Your Future?”

http://helix.nature.com/webmatters/agents/agents.html

ontologies
Ontologies
  • Machine readable semantic specifications.
    • Include terms, relations, and inference rules
    • What does “capital” mean?
      • Seat of government (Tallahassee, Harrisburg, Austin)
      • An upper-case letter
      • monies, securities, investments, etc…
      • the top of a column or pillar.
  • XML is Not Enough!!!
    • Allows definition of syntax, but not semantics (meaning)
    • Can be considered the “Assembly Language” of the Web.
omg initiatives
OMG Initiatives
  • OMG Agent Platform Special Interest Group (SIG)
    • extend the OMG Object Management Architecture (OMA) to better support agent technology
    • identify and recommend new OMG specifications in the agent area
    • recommend agent-related extensions to existing and emerging OMG specifications
    • promote standard agent modeling techniques
    • see http://www.objs.com/agent/index.html
  • OMG Ontology Working Group
    • Align the domain modeling activities of OMG with the Semantic Web initiative of the World Wide Web Consortium and with related ontology development projects such as DARPA DAML and IEEE SUO (Standard Upper Ontology).
d arpa a gent m arkup l anguage
DARPA Agent Markup Language
  • Machine-Readable Ontologies & Annotation (markup)
  • Aimed at “Resources”, Not just web-pages
    • Sensors
    • Services
    • Appliances
  • Lots of industry Buzz*
    • Scientific American
    • IEEE Distributed Systems
    • New York Times
    • ZDNet

*See http://www.daml.org/inthenews.html

daml basic idea

DAML

annotation

queries

web

pages

links

web crawlers

DAML

ontologies

annotate

manually or

semi-automatically

queries

DAML

annotation

links

queries

schema

RDBMS

queries

data

web pages, databases, legacy software, devices, sensors...

have annotations linking their terms to ontologies

agents

DAML: Basic Idea
daml annotation extreme metadata

Evolution of Metadata

explicit semantic agreements via machine-readable ontologies

implicit semantic agreements on paper!

Subject verb object

semantics for

selected sentences

document

parsing info

XML

schema

Full semantics

for all content

keywords

browser

web crawler

XML

parsers

agents

(near-term)

agents

(future)

DAML Annotation: Extreme Metadata
daml program
DAML Program
  • Main DAML website = www.daml.org
  • Duration: August 2000 to Fall 2002
  • Approach:
    • MIT W3C semantic web activity
      • http://www.w3c.org/2001/sw/
      • “The semantic Web and its languages” in IEEE Intelligent Systems, November/December 2000, pages 67-73 available at http://www.ksl.Stanford.EDU/projects/DAML/
    • Extend XML/RDF
      • represent ontologies
      • annotate web pages and other information with links to ontologies
daml program cont
DAML Program (Cont.)
  • 17 research teams and 1 integration team
    • industry, academia and World Wide Web Consortium
    • expertise in AI knowledge representation, logic and web technologies
    • cooperation with European Union IST Program
      • www.daml.org/committee/
  • DAML language definition
    • Ontology Definition
    • Rules Definition
daml program cont1
DAML Program (Cont.)
  • DAML tools
    • ontology development and verification
    • web page annotation
    • dynamic composition of agent services
    • distributed query processing and inference
    • ontology translation
  • DAML trial applications
    • Government: Intelink, Center for Army Lessons Learned
    • Commercial: e-commerce, information retrieval
the origins of daml

DAML

RDFS

RDF

XML

The Origins of DAML
  • Extensible Markup Language (XML)
    • provides syntactic interoperability
    • depends on implicit semantic agreements
  • Resource Description Framework (RDF)
    • designed to represent metadata for web resources in an XML syntax
    • triples:
  • RDF Schema (RDFS)
    • adds OO concepts: class and subclass

<shoeGen:GovermentOrganization rdf:ID="DARPA”/>

<shoeGen:OrganizationHomePage rdf:about="http://www.darpa.mil/">

<shoeProj:authorOrg rdf:resource="#DARPA" />

</shoeGen:OrganizationHomePage>

* For more information see www.w3.org

status of daml
Status of DAML
  • DAML+Oil (ontology)
    • released January 2001 - latest revision March 2001
    • language specifications and documentation:
      • http://www.daml.org/2001/03/daml+oil-index.html
    • design rationale
      • http://www.cs.man.ac.uk/~horrocks/Slides/index.html
  • DAML-L (logic)
    • rule representation and reasoning
    • development in progress
uml based ontology toolset ubot
UML-Based Ontology Toolset (UBOT)
  • We are applying:
    • graphical modeling and formal verification techniques from software engineering
    • text extraction from natural language processing
    • lexical semantic resources from cognitive science
  • to build a tool-set that supports
    • creation, extension and consistency checking of DAML ontologies
    • DAML annotation of information resources for agents
  • intended for users who have minimal training in knowledge representation and agent theory
    • see http://ubot.lockheedmartin.com/
ubot team
UBOT Team
  • Lockheed Martin Management & Data Systems
    • architecture, development and integration
  • Versatile Information Systems (Northeastern University)
    • formal verification of UML
  • Lockheed Martin Advanced Technology Center
    • field test of DAML and UBOT
  • Kestrel Institute
    • automated formal methods
ubot architecture ontology engineering

DAML Ontology

Engineer

UBOT

XMI

models

UML

DAML

Translation

UML GUI

Consistency

checking

results

XMI

models

Extended

DAML

ontologies

UML

Formalization

Baseline

DAML

ontologies

Slang

models

Semantic

inconsistencies

Specware

UBOT Architecture: Ontology Engineering
ubot architecture annotation

UBOT

UML

DAML

Translation

XMI

UML GUI

corrected

annotation

uncorrected

annotation

automatically

generated

Extraction

to DAML

Translation

DAML annotated text or web pages

DAML

Annotator

DAML

Ontologies

Text or

web pages

Text Extraction

UBOT Architecture: Annotation
ubot architecture cots components
UBOT Architecture: COTS Components
  • UML GUI
    • Tau UML Suite (Telelogic)
  • Specware (Kestrel Institute)
    • supports ontology consistency checking via formal methods
    • SNARK theorem prover (SRI)
  • Text Extraction
    • AeroText (LM M&DS)
      • extracts entities (e.g. people, organizations, etc.) from natural language
      • recognizes relationships between entities (e.g. [organization]hired[person] )
      • developed for the U.S. Intelligence Community
      • 12 years experience with sophisticated linguistic processing
      • many fielded applications
text extraction aerotext
Text Extraction: AeroText

Document Window

Extraction Display